Big data essential for customer loyalty measurements
Deputy Director of the Cambridge Service Alliance, Dr Mohamed Zaki, discusses the pitfalls of relying on simplistic numerical values to measure customer loyalty in an article published in Marketing Week.
Improving the customer experience is a top priority of executives world-wide. Dr Zakis says that despite this need: "knowing just what to do and how to do go about it is challenging especially with the extensive volume of big data generated from customer experience systems.
"Our research is applying big data techniques to customer experience survey data to offer significant insights to identify pain points and prioritise actions to improve customer experience. Contextualised in B2B settings, we aim to, firstly, provide a new customer experience analytic approach that combines quantitative and qualitative measures.
"Secondly, we are demonstrating the usefulness of a longitudinal customer experience analytic that pinpoints the sources of friction, root causes of complaints, suggestions for improvements across touchpoints and prioritising actions to enhance customer experience. As a result, we can identify segments of customers that are vulnerable to leaving by using longitudinal data analysis.
"Our approach offers firms another option in the toolkit to utilise existing data more effectively in order to provide rich insights and specific actions designed to improve customer experiences."
Dr Zaki uses an interdisciplinary approach of data science techniques in his research to address a range of real problems experienced by organisations. In particular, his research develops novel data science methods to measure customer experience, develop loyalty predictive models and analyse sensor data to classify product failures in manufacturing.